<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Digital Transformation and Administration Innovation</JournalTitle>
      <Issn></Issn>
      <Volume>4</Volume>
      <Issue>Serial Number 14</Issue>
      <PubDate PubStatus="epublish">
        <Year>2026</Year>
        <Month>07</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Behavioral Pattern Analysis of Customers in Value Co-Creation Processes in the Omnichannel Retail Industry</ArticleTitle>
    <VernacularTitle>Behavioral Pattern Analysis of Customers in Value Co-Creation Processes in the Omnichannel Retail Industry</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>16</LastPage>
    <ELocationID EIdType="doi">10.61838/dtai.265</ELocationID>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2025</Year>
        <Month>12</Month>
        <Day>28</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;This study was conducted with the aim of identifying and classifying customers’ behavioral patterns in omnichannel retailing and explaining their role in value co-creation. Given the heterogeneity of consumer behavior in omnichannel environments, the present study seeks to reveal hidden differences among customers based on the level of interaction, shopping experience, and participation in value-creating processes. Therefore, the study adopted a descriptive–analytical approach with a data mining orientation. Data related to 1,000 active customers within an omnichannel retail platform were collected and analyzed in RapidMiner using clustering and classification techniques. To determine the optimal cluster structure, the Davies–Bouldin Index was employed alongside the K-Means and X-Means algorithms. The findings demonstrated that customers are heterogeneous in terms of participation level, information sharing, channel usage, and value co-creation, and they can be categorized into three distinct clusters: mainstream customers, active value co-creators, and passive customers. The results further indicated that the group of active co-creators generates the highest level of interaction and value creation for retailers, whereas passive customers require trust-building, education, and simplification of the shopping experience. Consequently, omnichannel retailing is not only a competitive necessity but also a platform for shared value creation, enhancement of customer experience, and development of behavior-based segmentation strategies.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Omnichannel retailing</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">value co-creation</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">customer behavior</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">customer participation</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">behavioral segmentation</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://journaldtai.com/index.php/jdtai/article/download/265/249</ArchiveCopySource>
  </Article>
</ArticleSet>
